粗大廃棄物の自律リサイクルに向けたマルチスペクトル画像AIロボットシステムの初期教訓
First Lessons Learned of an Artificial Intelligence Robotic System for Autonomous Coarse Waste Recycling Using Multispectral Imaging-Based Methods
粗大廃棄物の選別を自動化するため、UV・可視・近赤外・短波赤外のマルチスペクトル画像で材料分類を行い、油圧重機をAIで自律制御するシステムを検討した。
著者: Timo Lange, Ajish Babu, Philipp Meyer, Matthis Keppner, Tim Tiedemann, Martin Wittmaier, Sebastian Wolff, Thomas Vögele
分類: cs.CV, cs.LG, cs.RO
原文アブストラクト
Current disposal facilities for coarse-grained waste perform manual sorting of materials with heavy machinery. Large quantities of recyclable materials are lost to coarse waste, so more effective sorting processes must be developed to recover them. Two key aspects to automate the sorting process are object detection with material classification in mixed piles of waste, and autonomous control of hydraulic machinery. Because most objects in those accumulations of waste are damaged or destroyed, object detection alone is not feasible in the majority of cases. To address these challenges, we propose a classification of materials with multispectral images of ultraviolet (UV), visual (VIS), near infrared (NIR), and short-wave infrared (SWIR) spectrums. Solution for autonomous control of hydraulic heavy machines for sorting of bulky waste is being investigated using cost-effective cameras and artificial intelligence-based controllers.